Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

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This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

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13 p.

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Zhang, J.; Chowdhury, S.; Messac, A. & Hodge, B. M. August 1, 2013.

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Description

This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

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13 p.

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  • To be presented at the ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 4-7 August 2013, Portland, Oregon

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  • Report No.: NREL/CP-5500-57647
  • Grant Number: AC36-08GO28308
  • Office of Scientific & Technical Information Report Number: 1090955
  • Archival Resource Key: ark:/67531/metadc839069

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  • August 1, 2013

Added to The UNT Digital Library

  • May 19, 2016, 9:45 a.m.

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  • April 3, 2017, 7:48 p.m.

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Zhang, J.; Chowdhury, S.; Messac, A. & Hodge, B. M. Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint, article, August 1, 2013; Golden, Colorado. (digital.library.unt.edu/ark:/67531/metadc839069/: accessed August 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.